Machine Learning Engineer

Job Summary

AI/ML Engineer

Python

Roles & Responsibilities

1. Model Development & Training

• Design, train, and fine-tune

  AI/ML models

  , especially

  Generative AI

  and

  Large Language Models (LLMs)

  , to address specific use cases.
• Build conversational AI solutions and chatbots using frameworks such as

  LangChain

  ,

  RAG (Retrieval-Augmented Generation)

  , and

  Chain-of-Thought (COT) prompting

  .
• Apply advanced techniques, including

  embeddings

  , fine-tuning, and custom prompting strategies.
• Incorporate

  REACT (Retrieve, Extract, Adapt, Construct, Think)

  methods to enhance model capabilities.
• Develop scalable AI solutions to integrate seamlessly into production environments.

1. Data Handling

• Manage

  large-scale datasets

  for AI/ML applications, ensuring data quality, transformation, and normalization.
• Conduct

  data analysis, preprocessing, and munging

  to extract valuable insights.
• Implement scalable data engineering workflows for model development and production.

1. Cloud AI/ML Deployment

• Deploy, manage, and optimize AI models on

  Google Cloud Platform (GCP)

  (or other cloud platforms like AWS/Azure).
• Leverage GCP services such as Vertex AI, BigQuery, Cloud Functions, and Dataflow for AI workflows.

1. Collaboration & Solutioning

• Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to deliver AI-driven solutions.
• Integrate models with client-facing applications, ensuring end-to-end implementation.
• Support scalable development through

  Docker

  for containerization (a plus).

1. Continuous Improvement

• Stay updated with the latest advancements in AI, ML, and Generative AI frameworks, tools, and methodologies.
• Proactively learn new technologies and apply them to improve processes and solutions.

1. Web Scraping (Optional but Preferred)

• Implement

  web scraping

  solutions to gather data from unstructured sources for model training and validation.

Required Skills & Qualifications

• 3-6 years

  of experience in AI/ML model development, training, and fine-tuning.
• Strong programming skills in

  Python

  and

  SQL

  .
• Hands-on experience with

  Generative AI

  ,

  LLMs

  , and

  NLP techniques

  .
• Experience working with

  LangChain

  ,

  RAG frameworks

  , and advanced prompting strategies.
• Proficiency in Chain-of-Thought (

  CoT

  ) prompting, Model Context Protocol

  (MCP)

  , and Agent-to-Agent (

  A2A

  ) orchestration
• Proficiency in

  embeddings

  and fine-tuning models for specific tasks.
• Strong understanding of

  machine learning algorithms

  and statistical analysis.
• Experience working with

  large datasets

  and scalable data processing workflows.
• Hands-on experience with

  GCP (Vertex AI, BigQuery)

  or other cloud platforms (AWS/Azure).
• Knowledge of

  Docker

  for deployment and containerization.
• Solid skills in

  data cleaning, transformation, and normalization

  for data integrity.

Preferred Skills

• Familiarity with

  Reinforcement Learning from Human Feedback (RLHF)

  .
• Understanding of

  COT (Chain-of-Thought) prompting

  .
• Proficiency in

  REACT (Retrieve, Extract, Adapt, Construct, Think)

  frameworks.
• Experience in

  web scraping

  techniques.

Key Attributes

• Strong analytical and problem-solving abilities.
• Ability to work independently as well as collaboratively in a team environment.
• Excellent communication skills to interact with stakeholders and cross-functional teams.
• Proactive attitude to learn and adopt new AI technologies and frameworks.